The use of direct current distribution systems in delivering scalable charging infrastructure for battery electric vehicles

The use of low voltage direct current (LVDC) distribution is becoming recognised as a technology enabler that can be used to efficiently network native DC generators with DC loads, offer improved power sharing capabilities, reduce power system material resource requirements and enhance the performance of variable speed machinery. Practical deployment opportunities for LVDC range from small-scale microgrids in the context of energy for development to sophisticated, modern building-level power distribution systems for commercial office spaces, manufacturing applications and industrial processes. However, the incumbent AC distribution system benefits from existing technical product and safety standards, which makes the early adoption of LVDC systems challenging from a risk and cost perspective. Concurrently, the demand for native DC loads such as Battery Electric Transportation Systems is growing. This is especially significant in the area of private electric vehicles (EVs), taxis and buses, but the prospect of electric trucks, ferries and shortrange aircraft are also tangible opportunities. The success of this electric transport revolution depends on several factors, one of which is the availability of battery charging infrastructure that can cost effectively integrate with the existing electrical network, deliver adequate energy transfer rates and adapt to the rapid technical development of this industry. This thesis explores the application of two, novel LVDC distribution systems for the development of scalable EV charging networks; where charging infrastructure has the ability to scale with increasing EV adoption and has a lower risk of becoming a stranded asset in the future. The modelling is supported by real, rapid DC charger utilisation data from the national charging network in Scotland, comprising over 192 chargers and 400,000 charging events. During the work of this thesis, it was found that a combined heat and power (CHP) system can economically support short duration charging scenarios by providing additional power capacity in a congested electrical grid. In this case the highest system efficiency and Net Present Value (NPV) is achieved with a fuel cell directly connected to the DC charging network, compared to other gas reciprocating CHP options. Furthermore, the proposition of a reconfigurable LVDC charging network, interfaced to the public AC distribution network, reduces the capital outlay, offers a higher NPV and improved scalability compared to other charging solutions. For charging system designers and operators, it was found that rapid DC chargers can be classified by specific locations, each possessing a distinct Gaussian arrival pattern and Gamma distribution for charging energy delivered.The use of low voltage direct current (LVDC) distribution is becoming recognised as a technology enabler that can be used to efficiently network native DC generators with DC loads, offer improved power sharing capabilities, reduce power system material resource requirements and enhance the performance of variable speed machinery. Practical deployment opportunities for LVDC range from small-scale microgrids in the context of energy for development to sophisticated, modern building-level power distribution systems for commercial office spaces, manufacturing applications and industrial processes. However, the incumbent AC distribution system benefits from existing technical product and safety standards, which makes the early adoption of LVDC systems challenging from a risk and cost perspective. Concurrently, the demand for native DC loads such as Battery Electric Transportation Systems is growing. This is especially significant in the area of private electric vehicles (EVs), taxis and buses, but the prospect of electric trucks, ferries and shortrange aircraft are also tangible opportunities. The success of this electric transport revolution depends on several factors, one of which is the availability of battery charging infrastructure that can cost effectively integrate with the existing electrical network, deliver adequate energy transfer rates and adapt to the rapid technical development of this industry. This thesis explores the application of two, novel LVDC distribution systems for the development of scalable EV charging networks; where charging infrastructure has the ability to scale with increasing EV adoption and has a lower risk of becoming a stranded asset in the future. The modelling is supported by real, rapid DC charger utilisation data from the national charging network in Scotland, comprising over 192 chargers and 400,000 charging events. During the work of this thesis, it was found that a combined heat and power (CHP) system can economically support short duration charging scenarios by providing additional power capacity in a congested electrical grid. In this case the highest system efficiency and Net Present Value (NPV) is achieved with a fuel cell directly connected to the DC charging network, compared to other gas reciprocating CHP options. Furthermore, the proposition of a reconfigurable LVDC charging network, interfaced to the public AC distribution network, reduces the capital outlay, offers a higher NPV and improved scalability compared to other charging solutions. For charging system designers and operators, it was found that rapid DC chargers can be classified by specific locations, each possessing a distinct Gaussian arrival pattern and Gamma distribution for charging energy delivered

Development of a power monitoring and control system to provide demand side management of electric vehicle charging activity.

Due to the recent inflow of Electric Vehicles (EVs) to the automobile market, new concerns have risen with respect to the additional electrical load and the resultant effects on an overloaded electric grid. Either for convenience purposes or possibly necessity due to limited electric range on EVs, some EV owners may desire to charge their EV while at work in addition to charging at home. These forward-thinking daytime charging providers are typically Commercial and Industrial (C&I) electric ratepayers, or other large electric consumers which constitute the majority of businesses, shopping centers, academic campuses and manufacturing facilities. Increased electricity consumption due to EV charging activity results in higher electricity costs due to differences in the billing structures between residential and C&I electric ratepayers. Therefore, it is beneficial to the EVSE charging provider to minimize charging activity around peak demand periods which would result in lower electrical costs overall. A solution is developed that can provide this control without creating a nuisance to electric vehicle owners since EV charging demand is somewhat inelastic due to range anxiety. The primary objective of the research detailed in this dissertation is to develop a novel demand side management system for monitoring the peak demand of commercial time-of-day electric ratepayers that cost effectively predicts and controls electric vehicle charging during peak demand periods. This objective is achieved, therefore confirming the hypothesis that such a system can provide cost and demand benefits to forward-thinking commercial electric ratepayers that provide daytime charging capabilities. This work proposes and evaluates a novel Power Monitoring and Control System (PMCS) that can be implemented at C&I EV charging locations to minimize or eliminate the negative impacts of charging electric vehicles at the workplace in C&I environments. Operation of the PMCS begins by forecasting electrical demand in advance of every 15 minute demand interval throughout the day. The forecast is generated using an artificial neural network and a number of input data streams. Electrical demand has been shown to correlate well with weather data such as temperature and dew point. Therefore, using those measurements along with a date and time stamp, and historical electrical demand measurements, a highly accurate forecast for the following 15-minute demand interval was achieved. From that forecast, the number of EV charging stations that may be active, without the chance of creating new electrical demand peaks, is calculated. Finally, the forecast is then used to properly schedule EV charging activity so that electrical demand peaks can be avoided but charging activity is maximized. The avoidance of charging activity at or near peaks in electrical demand results in lower total electric costs associated with the charging process. The final design was implemented in an EV charging testbed at the University of Louisville and data was collected to verify the operation and performance of the PMCS. With a properly designed scheduling and prioritization control algorithm, increases in electrical demand and associated costs are limited to the error in the forecasting algorithm used for predicting electrical demand levels. The final design of the forecasting algorithm results in a mean absolute percent error of 0.02% to 0.08% in the electrical demand forecast. This corresponds to approximately 3 to 10 kVA of error in electrical demand. Taking this error into account, total cost of charging several EVs is reduced by nearly 90%. Furthermore, for scenarios where there are several more electric vehicles requiring charge than there are charging stations available, several scheduling algorithms are presented in an attempt to minimize the total processing time required for completing all charging transactions

Advances on Smart Cities and Smart Buildings

Modern cities are facing the challenge of combining competitiveness at the global city scale and sustainable urban development to become smart cities. A smart city is a high-tech, intensive and advanced city that connects people, information, and city elements using new technologies in order to create a sustainable, greener city; competitive and innovative commerce; and an increased quality of life. This Special Issue collects the recent advancements in smart cities and covers different topics and aspects

Solar Power System Plaing & Design

Photovoltaic (PV) and concentrated solar power (CSP) systems for the conversion of solar energy into electricity are technologically robust, scalable, and geographically dispersed, and they possess enormous potential as sustainable energy sources. Systematic planning and design considering various factors and constraints are necessary for the successful deployment of PV and CSP systems. This book on solar power system planning and design includes 14 publications from esteemed research groups worldwide. The research and review papers in this Special Issue fall within the following broad categories: resource assessments, site evaluations, system design, performance assessments, and feasibility studies

City of Vancouver EV Infrastructure Strategy Report

The role of the local government in supporting the growth and maintenance of a strong plug‐in electric vehicle market in Vancouver is evaluated in this report. This report identifies areas of action in which a local government, such as Vancouver, can impact their region based on a thorough understanding of the current plug‐in vehicle market, international demonstration projects, and research efforts. Specifically, workplace and public charging is needed to reinforce and fulfill the gaps from home‐based charging in dense urban regions. Local government can encourage investments in workplace and public charging by providing clear regional guidelines for installers and customers, providing appropriate incentives to businesses, allowing for an innovative marketplace in the vehicle charging industry, and collaborating with the regional utility to identify specific opportunities for optimization and encouragement of utility rates and vehicle‐grid interactions

Microgrids: Planning, Protection and Control

This Special Issue will include papers related to the planning, protection, and control of smart grids and microgrids, and their applications in the industry, transportation, water, waste, and urban and residential infrastructures. Authors are encouraged to present their latest research; reviews on topics including methods, approaches, systems, and technology; and interfaces to other domains such as big data, cybersecurity, human–machine, sustainability, and smart cities. The planning side of microgrids might include technology selection, scheduling, interconnected microgrids, and their integration with regional energy infrastructures. The protection side of microgrids might include topics related to protection strategies, risk management, protection technologies, abnormal scenario assessments, equipment and system protection layers, fault diagnosis, validation and verification, and intelligent safety systems. The control side of smart grids and microgrids might include control strategies, intelligent control algorithms and systems, control architectures, technologies, embedded systems, monitoring, and deployment and implementation

State-of-the-Art Assessment of Smart Charging and Vehicle 2 Grid services

Electro-mobility – especially when coupled smartly with a decarbonised grid and also renewable distributed local energy generation, has an imperative role to play in reducing CO2 emissions and mitigating the effects of climate change. In parallel, the regulatory framework continues to set new and challenging targets for greenhouse gas emissions and urban air pollution. • EVs can help to achieve environmental targets because they are beneficial in terms of reduced GHG emissions although the magnitude of emission reduction really depends on the carbon intensity of the national energy mix, zero air pollution, reduced noise, higher energy efficiency and capable of integration with the electric grid, as discussed in Chapter 1. • Scenarios to limit global warming have been developed based on the Paris Agreement on Climate Change, and these set the EV deployment targets or ambitions mentioned in Chapter 2. • Currently there is a considerable surge in electric cars purchasing with countries such as China, the USA, Norway, The Netherlands, France, the UK and Sweden leading the way with an EV market share over 1%. • To enable the achievement of these targets, charging infrastructures need to be deployed in parallel: there are four modes according to IEC 61851, as presented in Chapter 2.1.4. • The targets for SEEV4City project are as follow: o Increase energy autonomy in SEEV4-City sites by 25%, as compared to the baseline case. o Reduce greenhouse gas emissions by 150 Tonnes annually and change to zero emission kilometres in the SEEV4-City Operational Pilots. o Avoid grid related investments (100 million Euros in 10 years) by introducing large scale adoption of smart charging and storage services and make existing electrical grids compatible with an increase in electro mobility and local renewable energy production. • The afore-mentioned objectives are achieved by applying Smart Charging (SC) and Vehicle to Grid (V2G) technologies within Operational Pilots at different levels: o Household. o Street. o Neighbourhood. o City. • SEEV4City aims to develop the concept of 'Vehicle4Energy Services' into a number of sustainable business models to integrate electric vehicles and renewable energy within a Sustainable Urban Mobility and Energy Plan (SUMEP), as introduced in Chapter 1. With this aim in mind, this project fills the gaps left by previous or currently running projects, as reviewed in Chapter 6. • The business models will be developed according to the boundaries of the six Operational Pilots, which involve a disparate number of stakeholders which will be considered within them. • Within every scale, the relevant project objectives need to be satisfied and a study is made on the Public, Social and Private Economics of Smart Charging and V2G. • In order to accomplish this work, a variety of aspects need to be investigated: o Chapter 3 provides details about revenue streams and costs for business models and Economics of Smart Charging and V2G. o Chapter 4 focuses on the definition of Energy Autonomy, the variables and the economy behind it; o Chapter 5 talks about the impacts of EV charging on the grid, how to mitigate them and offers solutions to defer grid investments; o Chapter 7 introduces a number of relevant business models and considers the Economics of Smart Charging and V2G; o Chapter 8 discusses policy frameworks, and gives insight into CO2 emissions and air pollution; o Chapter 9 defines the Data Collection approach that will be interfaced with the models; o Chapter 10 discusses the Energy model and the simulation platforms that may be used for project implementation

Combined power system planning and policy proposition for future electric vehicle charging infrastructure

This thesis was submitted for the award of Master of Philosophy and was awarded by Brunel University LondonIn order to achieve the UK Government’s legally bound framework of greenhouse gas reduction targets, the transport sector is undergoing drastic changes. The key action taken by the Department of Transport in addressing the issue was the introduction of Ultra-low emission vehicles (ULEV) concept. Office for Low Emission Vehicles (OLEV) was introduced to support early market for ULEV and development of efficient recharging network through Plugged-in Places programme. The massive deployment of EV charging stations across GB will have direct impact on GB power system as they require electricity supply for their operation. It is therefore deemed necessary to carry out investigations on the capacity of the network assets to handle this load and to develop policies to manage the future EV charging infrastructure efficiently. This thesis provides an overview of the EV technology introducing various technicalities behind EVs and the associated charging stations. The extended theory about interoperability between EVs and power networks is also presented. Investigation of an 11kV networked site and 66/11 kV networked area is performed to determine their potential in accommodating future EV charging infrastructure. A methodology has been proposed to carry out investigations in 11kV networked site. For analysis purpose both the real networks are modelled in detail using power system analysis software Electrical Transient Analyzer Programme (ETAP). Scottish and Southern Energy (SSE) and Northern Power Grid (NPG) are the owners of the distribution networks respectively. Collaboration with DNOs has taken place to collect the existing network data. Finally, a university based EV charging bays management policy has been proposed